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Valid and reliable measurement is critical to the assessment and evaluation of health interventions. However, few scholars have examined the psychometric properties of “gold standard” measures in carceral settings, and no research has explored the reliability, validity and factor structure of the 26-item World Health Organization Quality of Life (WHOQOL) BREF among older adults incarcerated in prison, a large and growing population marked by substantial chronic and life-limiting illness. This study aims to examine the reliability, validity and factor structure of the WHOQOL-BREF.

Secondary data from a large-scale study with older adults (age 45+) incarcerated in a Midwestern state were used (N = 499). Floor and ceiling effects were examined, as was the reliability of the measure (Cronbach's alpha). The structural validity of a four-factor and second-order four-factor model of the WHOQOL-BREF was examined using confirmatory factor analysis. Model data fit was examined using chi-square, standardized root mean square residual, comparative fit indices, Akaike information criterion and the Bayesian Information Criterion. Pearson product-moment correlation coefficients were also used to assess validity.

Results indicate adequate construct validity and reliability for the WHOQOL-BREF using the current sample. Model-data fit indexes also reveal adequate structure of the measure relative to other older adult samples. Non-random data and item exclusion are noteworthy limits, and future researchers are encouraged to co-conceptualize and operationalize life quality with older adults who are incarcerated.

To the best of the authors’ knowledge, this is the first study to explore the psychometric properties of the WHOQOL-BREF among older adults incarcerated in prison.

Existing research has ignored the perspectives of frontline managers (FLMs) in relation to the support they receive. This study aims to understand the extent to which and how other organisational actors support FLMs in their implementation of performance.

This article used a qualitative method (57 semi-structured interviews) in two Singapore public sector organisations to understand the types of support provided to FLMs. The interviewees came from various levels and the hierarchical sampling frame allowed for comparisons to be made across the cases.

The authors found that the HR department, superiors and peers signalled to FLMs the custom and practice of performance management (PM) that led to the FLMs not prioritising their PM responsibilities. Notably, the focus of the FLMs was on meeting operational needs rather than the PM process.

The authors add to the literature by examining the how the support from other organisational actors signalled to FLMs the importance of PM within their work group. This paper also explores how FLMs seek support and the type of support they want in their role.

Automatically extracting stance information from natural language texts is a significant research problem with various applications, particularly after the recent explosion of data on the internet via platforms like social media sites. Stance detection system helps determine whether the author agree, against or has a neutral opinion with the given target. Most of the research in stance detection focuses on the English language, while few research was conducted on the Arabic language.

This paper aimed to address stance detection on Arabic tweets by building and comparing different stance detection models using four transformers, namely: Araelectra, MARBERT, AraBERT and Qarib. Using different weights for these transformers, the authors performed extensive experiments fine-tuning the task of stance detection Arabic tweets with the four different transformers.

The results showed that the AraBERT model learned better than the other three models with a 70% F1 score followed by the Qarib model with a 68% F1 score.

A limitation of this study is the imbalanced dataset and the limited availability of annotated datasets of SD in Arabic.

Provide comprehensive overview of the current resources for stance detection in the literature, including datasets and machine learning methods used. Therefore, the authors examined the models to analyze and comprehend the obtained findings in order to make recommendations for the best performance models for the stance detection task.

Research on the organizational ramifications of chief executive officer (CEO) greed remains scarce. This study intends to fill this gap by examining the impact of CEO greed on an important yet risky corporate strategy, corporate tax avoidance (CTA). Drawing on upper echelons theory, the authors argue that greedier CEOs tend to engage in more CTA. The relationship is weaker when CEOs experienced economic recessions in their early career and stronger when CEOs are endowed with equity ownership of their respective firms.

The authors test the hypotheses with data from US public firms from 1997 to 2008 and employ the ordinary least square regression analysis to analyze the hypothesized relationships. The authors also test the robustness of the results by performing the two-stage least square regression and propensity score matching analyses.

The findings lend broad support to all the hypotheses. The authors find that greedier CEOs tend to engage in more CTA by paying lower corporate taxes. The impact of greed on CTA is attenuated when CEOs are recession CEOs and is exacerbated when CEOs own large numbers of firm shares.

This paper contributes to the upper echelons research by investigating a novel executive personal characteristic, greed, and its negative impact on an important organizational outcome. This paper also contributes to the growing tax research that recognizes the important role executives play in shaping corporate tax strategies.

This study aims to perform a systematic literature review to organize the abundance of information on employee relations (ER) and sustainable organizations. Moreover, this study identifies the research gaps by investigating the review of ER’ mediating and moderating variables and the relationship between ER and sustainable organizations.

This study is based on the systematic literature review methodology involving 257 studies in the final stage. The Scopus and Google Scholar databases with search criteria “employee relations” and “employee relations and sustainable organization” were used to achieve the research objective. After applying inclusion and exclusion criteria, researchers come to the distribution of the articles based on the subthemes, geographical region, types of methods, top authors with affiliation and complete research articles based on the citation. In the final stage, this study concluded with the conceptual model comprising mediators and moderators of ER as well as the mediating and moderating variables of the relationship between ER and sustainable organizations.

The reviewed literature shows that employee relation is an optimal strategy for retaining employees via proper disclosure of human resources (HRs) and ER Index. This study included the top six publishers, namely, Emerald, Elsevier, Sage, Springer, Taylor and Francis and Wiley Online Library, to do an exhaustive review on a specific topic. The findings indicate that after COVID-19, the ER index, HR disclosures and the sustainability of ER are among the new and required paradigm shifts needed to manage a crisis impact and perform productively. The mediator and moderator variables that can improve employee–employer relationships are organizational trusts, organizational justice, perceived job satisfaction, organizational structure and firm ownership. On the other hand, variables that mediate and moderate the relationship between ER and sustainable organizations are organizational climate, organization trust, organization culture, perceived organization support, psychological empowerment, firm ownership, leadership behavior and attitude, respectively. The findings concluded that harmonious and cordial ER are pertinent in building sustainable organizations and accomplishing organizational goals.

The mediating and moderating variables that have been identified can be helpful for enthusiastic researchers in contributing to empirical research. Practitioners and managers can use the findings in making an effective organizational model that develops good employee–employer relationships and helps create a culture of trust and harmony. This study focuses on exploring the variables of ER, which strengthens employee–employer relationships and supports organizations to stay agile and attain sustainability to endure in the future.

This study insights on the specific mediating and moderating variables of ER and sustainable organizations. Till date, studies exploring constructs of ER and sustainable organizations are still in deficit. Better employee relation reflects and leads to a more resilient organization. Future researchers should explore the connection between pandemics and ER which is done insufficiently in the present time.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

Criminals have quickly discovered the advantage of crypto assets, with its pseudo-anonymity, untraceability and the ability to freely exchange crypto assets across borders, which makes it an ideal tool for money laundering activities. Switzerland has a technology-neutral framework, and crypto assets are regulated by the existing anti-money laundering (AML) legislation. The purpose of this paper is to gain insights into the industry adoption of measurements to prevent money laundering through crypto assets and if they are compliant with national and international AML regulations.

Semi-structured expert interviews were conducted with participants having expertise in compliance, AML and crypto assets with focus on Switzerland. The interviews were analyzed using the thematic analysis.

The experts have a general consensus that Switzerland is a pioneer when it comes to regulating crypto assets. It is perceived that legislations are released without industry consultation and that AML processes for fiat transactions also work for crypto assets, which is not the case. The results show that the industry wants a consortium to fight money laundering in crypto assets in Switzerland. The current measures to identify money laundering are not optimal, yet, it is the best solution and according to national and international regulations the businesses are perceived to be compliant.

This paper offers new insights on the challenges of AML regulations in crypto assets, given the limited information available. It also provides good practice examples for addressing these challenges, benefiting policymakers, regulators and practitioners in the crypto asset ecosystem.

A flexible manufacturing system (FMS) helps improve the system’s performance, thus increasing its overall competitiveness. FMS is an essential component of Industry 4.0 (I4.0), which has revolutionized the way firms manufacture their products. This study aims to investigate the diverse focus of the research being published over the years and the direction of scholarly work in applying FMSs in business and management.

A total of 1,096 bibliometric data were extracted from the Scopus database from the years 2001 to 2021. A systematic review and bibliometric analysis were performed on the data and related articles for performance measurement and scientific mapping on the FMS themes.

Based on co-keyword, the study reveals four major themes in the FMS field: mathematical models and quantitative techniques, scheduling and optimization techniques, cellular manufacturing and decision-making in FMSs. Based on bibliometric coupling on 2018–2021 bibliometric data, four themes emerged for future research: scheduling problems in FMS, manufacturing cell formation problem, interplay of FMS with other latest technologies and I4.0 and FMS.

The originality lies in answering the following research questions: What are the most highlighting themes in FMS, and how have they evolved over the past 20 years (2001–2021)? What topics have been at the forefront of research in FMS in the past five years (2016–2021)? What are the promising avenues of research in FMS?